Probabilistic Survival Models is a statistical modeling framework that belongs to the class of survival analysis methods and distinguishes itself by explicitly quantifying uncertainty in time-to-event predictions through probabilistic distributions over survival outcomes.
537
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54.8K
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1.4K
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713
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Publications per year
2017–2026
108
Parents
Publications
537
Statistical Models Based on Counting Processes
Xavier Bry, Per Kragh Andersen, Ørnulf Borgan et al. · Population · 1997 · 2.9K citations
Modelling for Survival Data in Medical Research
Technometrics · 1995 · 2.2K citations
Survival Analysis: A Self-Learning Text
Mark Carpenter · Technometrics · 1997 · 1.4K citations
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1–5 of 1.4K
Institutions
713
Harvard University
Cambridge, United States
15 h-index
57 publications
2.1K citations
University of Michigan
Ann Arbor, United States
12 h-index
19 publications
659 citations
Universidade de São Paulo
São Paulo, Brazil
11 h-index
30 publications
1.1K citations
Inserm
Paris, France
10 h-index
18 publications
490 citations
Universidade Federal de Pernambuco
Recife, Brazil
9 h-index
16 publications
515 citations
The Ohio State University
Columbus, United States
8 h-index
7 publications
735 citations
University of Washington
Seattle, United States
8 h-index
9 publications
1.4K citations
National Cancer Institute
Bethesda, United States
8 h-index
26 publications
3.1K citations
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- Statistics in Medicine
42 publications · 2.7K citations
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- Journal of the American Statistical Association
27 publications · 8.8K citations
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- Biometrics
26 publications · 4K citations
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- Technometrics
20 publications · 8.6K citations
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- Biometrika
17 publications · 2.5K citations
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